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Claude 0f15b28ea3 Add docs, CI workflows, agent config, and supporting files

- Add MkDocs documentation with API reference for the CLI module
- Add CI/CD and Claude Code review GitHub Actions workflows
- Add Dependabot and Renovate configuration for dependency updates
- Add .claude settings, agents, and local-qa skill with QA script
- Add AGENTS.md with repository guidelines and CLAUDE.md symlink
- Update README.md with installation, usage examples, and commands

https://claude.ai/code/session_01YW3YHru8wRH9dvHnBX7xf1

2026-03-28 14:00:48 +00:00

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API Reference

This section contains the complete API documentation for mt5cli.

Modules

The mt5cli package consists of the following modules:

CLI

Command-line interface module providing typer-based commands for exporting MetaTrader 5 data to CSV, JSON, Parquet, and SQLite3 formats.

Architecture Overview

The package follows a simple architecture built on top of pdmt5:

CLI Layer (cli.py): Typer application with subcommands for each data type, custom Click parameter types for datetime/timeframe/tick flags parsing, and format detection/export utilities.
Data Layer (via pdmt5): Uses Mt5DataClient and Mt5Config from the pdmt5 package for all MetaTrader 5 data access.

Usage Guidelines

All modules follow these conventions:

Type Safety: All functions include comprehensive type hints
Error Handling: User-friendly error messages via typer
Documentation: Google-style docstrings with examples
Validation: Custom Click parameter types for input validation

Quick Start

# Export account information to CSV
mt5cli -o account.csv account-info

# Export EURUSD H1 rates to Parquet
mt5cli -o rates.parquet rates-from --symbol EURUSD --timeframe H1 \
  --date-from 2024-01-01 --count 1000

# Export ticks to JSON
mt5cli -o ticks.json ticks-from --symbol EURUSD \
  --date-from 2024-01-01 --count 500 --flags ALL

# Export to SQLite3 with custom table name
mt5cli -o data.db --table symbols symbols --group "*USD*"

Python API

from mt5cli import detect_format, export_dataframe
import pandas as pd

# Detect output format from file extension
fmt = detect_format(Path("output.parquet"))  # Returns "parquet"

# Export a DataFrame
df = pd.DataFrame({"symbol": ["EURUSD"], "bid": [1.1234]})
export_dataframe(df, Path("output.csv"), "csv")

Examples

See individual module pages for detailed usage examples and code samples.

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